
Ultimate access to all questions.
Which of the following best describes the main difference between unsupervised learning and supervised learning?
A
Unsupervised learning involves training a model on labeled data, while supervised learning involves training a model on unlabeled data.
B
Unsupervised learning involves training a model to make predictions, while supervised learning involves training a model to classify data.
C
Unsupervised learning involves training a model to learn from the data itself, while supervised learning involves training a model using explicit guidance from a human.
D
Unsupervised learning involves training a model to maximize a reward signal, while supervised learning involves training a model to minimize a loss function.
Explanation:
Correct Answer: C
Unsupervised learning involves training a model to discover data patterns without explicit guidance, while supervised learning involves training a model to make predictions or classify data using labeled examples.
A is incorrect: This reverses the definitions. Unsupervised learning actually involves training on unlabeled data, while supervised learning uses labeled data.
B is incorrect: Unsupervised learning recognizes data patterns without an explicit/predefined target, not necessarily to "classify" - that's typically a supervised task. Unsupervised learning may involve clustering or dimensionality reduction.
D is incorrect: This describes reinforcement learning (maximizing reward signal) versus supervised learning (minimizing loss function), not the distinction between unsupervised and supervised learning.